Package: Bayenet
Type: Package
Title: Robust Bayesian Elastic Net
Version: 0.4
Date: 2026-09-10
Authors@R: c( person("Xi", "Lu", role = c("aut", "cre"),
                      email = "xilu0521@gmail.com"),
              person("Cen", "Wu", role = "aut"))
Description: As heavy-tailed error distribution and outliers in the
        response variable widely exist, models which are robust to data
        contamination are highly demanded. Here, we develop a novel
        robust Bayesian variable selection method with elastic net
        penalty. In particular, the spike-and-slab priors have been
        incorporated to impose sparsity. An efficient Gibbs sampler has
        been developed to facilitate computation.The core modules of
        the package have been developed in 'C++' and R.
Depends: R (>= 3.5.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, stats, MCMCpack, base, gsl, VGAM, MASS, hbmem, SuppDists
RoxygenNote: 7.3.1
NeedsCompilation: yes
Packaged: 2026-10-24 11:40:42 UTC; root
Author: Xi Lu [aut, cre], Cen Wu [aut]
Maintainer: Xi Lu <xilu0521@gmail.com>
Repository: https://cran.r-universe.dev
Date/Publication: 2026-09-10 16:50:17 UTC
RemoteUrl: https://github.com/cran/Bayenet
RemoteRef: HEAD
RemoteSha: 5f29040d9d2496fe8d147b816c6e1509945f8167